Evaluation of parameters obtained from two systems of gait analysis
Bibliographic record
Abstract
Background The technical difficulties in utilising the force platform have stimulated the use and development of other gait systems. Therefore, this study aimed to compare the values of gait parameters obtained from a pressure‐sensitive walkway and from a treadmill in healthy dogs during walking. Methods Twelve healthy, privately owned, Labrador retriever dogs were used. During each trial, each dog was led across the pressure‐sensitive walkway utilising a loose leash to the right of the handler. The velocity was restricted to the range of 0.9 to 1.1 m/s and the acceleration between −0.15 and 0.15 m/s2. For the treadmill, each dog also walked with leash loose on the treadmill. The treadmill speed was maintained at 0.9m/s. The temporospatial variables, and percentage of body weight distribution/percentage of pressure were evaluated between the two gait systems. Results For both forelimbs and hind limbs, significant differences were found between stance percentage, which was higher on treadmill, and swing percentage and stride length/stance distance, which were higher on the pressure‐sensitive walkway. The duty factor value was 0.57 for the pressure‐sensitive walkway and 0.60 for treadmill. Clinical relevance Each gait system has limitations, but also advantages that must be considered depending upon the variable and animal to be evaluated. The gait parameters obtained from the Tekscan pressure‐sensitive walkway and Gait4Dog treadmill revealed differences in the temporospatial parameters between systems, but similarity in body‐weight distribution/pressure percentage.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".